Unmanned aerial vehicle battery data uploading communication monitoring method and device, computer equipment and storage medium

Abstract

The invention provides an unmanned aerial vehicle battery data uploading communication monitoring method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a battery uploading parameter of an unmanned aerial vehicle battery; performing hierarchical verification processing on the battery uploading parameter and a preset uploading parameter to obtain a battery uploading verification value; and sending a data uploading level adjusting signal to the unmanned aerial vehicle aggregation communicator according to the battery uploading verification value so as to adjust an uploading mode of the battery uploading parameters. After the battery uploading parameters are collected, the current battery operation state of the unmanned aerial vehicle battery is determined, then the battery uploading parameters are verified and compared with standard uploading parameters, the difference degree of battery operation uploading data of the unmanned aerial vehicle battery is conveniently determined, and finally the unmanned aerial vehicle battery is determined according to the difference degree of the battery operation uploading data. According to the method, the uploading mode of the unmanned aerial vehicle battery is adjusted to select the optimal uploading mode of the unmanned aerial vehicle battery, so that the conflict of uploading data during battery operation is avoided, and the battery data uploading efficiency is effectively improved.

Description

Technical Field

[0001] This disclosure relates to the field of drone battery technology, and in particular to a method, apparatus, computer equipment, and storage medium for monitoring and uploading drone battery data. Background Technology

[0002] The high energy density, high charge / discharge rate, and long lifespan of lithium batteries have led to their increasingly widespread application, especially in heavy-duty applications. In large unmanned aerial vehicle (UAV) systems, a single battery module is insufficient to meet the demands of long flight time and heavy payload, necessitating the use of multi-battery parallel power supply solutions.

[0003] However, existing multi-battery management systems for drones suffer from limited communication resources, primarily including: 1) Each battery module independently reports data via its BMS, causing CAN bus data congestion; 2) The UAV flight control system uses a standard CAN 2.0B bus (maximum bandwidth 1Mbps), and simultaneous reporting by multiple battery management units causes channel congestion; 3) During flight, battery parameters are sampled at high frequencies (typically 100Hz). Traditional frame formats are inefficient and cannot meet the requirements for real-time monitoring. 4) The UAV flight control and battery management share CAN bus resources, and excessive bandwidth consumption of battery data transmission affects the real-time performance of flight control. Summary of the Invention

[0004] The purpose of this disclosure is to overcome the shortcomings of the prior art and provide a method, apparatus, computer equipment, and storage medium for monitoring and transmitting UAV battery data uploads to effectively improve battery data upload efficiency.

[0005] The purpose of this disclosure is achieved through the following technical solution: A method for monitoring communication and uploading battery data from a drone, the method comprising: Obtain the battery upload parameters for the drone battery; The battery upload parameters are compared with preset upload parameters in a hierarchical verification process to obtain the battery upload verification value. Based on the battery upload verification value, a data upload adjustment signal is sent to the drone aggregation communicator to adjust the upload mode of the battery upload parameters.

[0006] In one embodiment, the process of acquiring the battery upload parameters of the drone battery includes: acquiring the drone battery's battery operation data, operation data fluctuation frequency, and the number of operation abnormality warnings.

[0007] In one embodiment, the battery upload parameters are subjected to hierarchical verification processing with preset upload parameters to obtain battery upload verification values, including: calculating the operation verification adjustment between battery operation data and preset operation data to obtain operation status adjustment; and / or calculating the fluctuation verification adjustment between operation data fluctuation frequency and preset fluctuation frequency to obtain fluctuation frequency adjustment; and / or calculating the abnormal verification adjustment between the number of operation abnormal warnings and preset warning number to obtain abnormal warning adjustment.

[0008] In one embodiment, a data upload adjustment signal is sent to the drone aggregation communicator based on the battery upload verification value to adjust the upload mode of the battery upload parameters, including: detecting whether the operating status adjustment is greater than a preset operating adjustment; when the operating status adjustment is greater than the preset operating adjustment, sending an emergency data upload signal to the drone aggregation communicator.

[0009] In one embodiment, the step of detecting whether the operating state adjustment is greater than a preset operating adjustment further includes: when the operating state adjustment is less than or equal to the preset operating adjustment, detecting whether the fluctuation frequency adjustment is greater than a preset frequency adjustment; and when the fluctuation frequency adjustment is greater than the preset frequency adjustment, sending a high-frequency data upload signal to the UAV aggregation communicator.

[0010] In one embodiment, after detecting whether the fluctuation frequency adjustment is greater than a preset frequency adjustment, the method further includes: when the fluctuation frequency adjustment is less than or equal to the preset frequency adjustment, detecting whether the operating state adjustment is greater than the static operating adjustment; when the operating state adjustment is greater than the static operating adjustment, sending a data intermediate frequency upload signal to the UAV aggregation communicator.

[0011] In one embodiment, the process of detecting whether the operational status adjustment is greater than the static operational adjustment further includes: when the operational status adjustment is less than or equal to the static operational adjustment, detecting whether the abnormal warning adjustment is less than or equal to a preset abnormal adjustment; and when the abnormal warning adjustment is less than or equal to the preset abnormal adjustment, sending a low-frequency data upload signal to the UAV aggregation communicator.

[0012] A drone battery data upload communication monitoring device is disclosed. The device employs the drone battery data upload communication monitoring method described in any of the above embodiments. The device includes a battery data acquisition module, an upload verification processing module, and an upload adjustment module. The battery data acquisition module acquires battery upload parameters of the drone battery. The upload verification processing module performs hierarchical verification processing on the preset upload parameters of the battery upload parameters to obtain a battery upload verification value. The upload adjustment module sends a data upload adjustment signal to the drone aggregation communicator based on the battery upload verification value to adjust the upload mode of the battery upload parameters.

[0013] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps: Obtain the battery upload parameters for the drone battery; The battery upload parameters are compared with preset upload parameters in a hierarchical verification process to obtain the battery upload verification value. Based on the battery upload verification value, a data upload adjustment signal is sent to the drone aggregation communicator to adjust the upload mode of the battery upload parameters.

[0014] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor: Obtain the battery upload parameters for the drone battery; The battery upload parameters are compared with preset upload parameters in a hierarchical verification process to obtain the battery upload verification value. Based on the battery upload verification value, a data upload adjustment signal is sent to the drone aggregation communicator to adjust the upload mode of the battery upload parameters.

[0015] Compared with the prior art, this disclosure has at least the following advantages: After collecting the battery upload parameters, the current battery operating status of the drone is determined. Then, the battery upload parameters are compared and verified with the standard upload parameters to determine the degree of difference in the uploaded battery data. Finally, based on the degree of difference in the uploaded battery data, the upload mode of the drone battery is adjusted to select the optimal upload method, avoid conflicts in the uploaded battery data, and effectively improve the battery data upload efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this disclosure and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a drone battery data upload communication monitoring method in one embodiment; Figure 2 This is a diagram of the CAN bus communication system architecture. Figure 3 This is a schematic diagram of the ABMA data structure; Figure 4 A hierarchical classification diagram of drone battery data; Figure 5 This is a diagram of a lightweight compression algorithm architecture; Figure 6 Choose a flowchart for the adaptive algorithm; Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0018] To facilitate understanding of this disclosure, a more complete description will be given below with reference to the accompanying drawings, which illustrate preferred embodiments of the present disclosure. However, this disclosure can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure.

[0019] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] This disclosure relates to a method for monitoring and uploading communication of drone battery data. In one embodiment, the method includes acquiring battery upload parameters of the drone battery; performing hierarchical verification processing on the battery upload parameters and preset upload parameters to obtain a battery upload verification value; and sending a data upload adjustment signal to the drone's aggregated communicator based on the battery upload verification value to adjust the upload mode of the battery upload parameters. After acquiring the battery upload parameters, the current battery operating state of the drone battery is determined. Then, the battery upload parameters are verified and compared with standard upload parameters to determine the degree of difference in the uploaded data. Finally, based on the degree of difference in the uploaded data, the upload mode of the drone battery is adjusted to select the optimal upload method, avoid conflicts in the uploaded data, and effectively improve the battery data upload efficiency.

[0022] Please see Figure 1This is a flowchart of a drone battery data upload and communication monitoring method according to an embodiment of the present disclosure. The drone battery data upload and communication monitoring method includes some or all of the following steps.

[0023] S100: Obtain the battery upload parameters for the drone battery.

[0024] In this embodiment, the battery upload parameter is the current battery operation data to be uploaded by the drone battery, that is, the battery upload parameter is the uploaded battery operation index of the drone battery, and the battery upload parameter corresponds to the operating status of the drone battery. By collecting the battery upload parameter, it is convenient to determine the operating status of the uploaded battery status index.

[0025] S200: Perform hierarchical verification processing on the battery upload parameters and preset upload parameters to obtain the battery upload verification value.

[0026] In this embodiment, the battery upload parameter is the current battery operation data to be uploaded for the drone battery, that is, the battery upload parameter is the uploaded battery operation index of the drone battery, and the battery upload parameter corresponds to the operating status of the drone battery. Collecting the battery upload parameter facilitates the determination of the operating status of the uploaded battery status index. The preset upload parameter is the standard uploaded battery operation data for the drone battery, that is, the preset upload parameter is the uploaded battery operation reference index of the drone battery, and the preset upload parameter corresponds to a specified operating status of the drone battery. Through hierarchical verification processing of the battery upload parameter and the preset upload parameter, it is easy to determine the differences in the current battery operation data to be uploaded for the drone battery, thereby facilitating the determination of whether there are differences in the operating status of the drone battery.

[0027] S300: Send a data upload adjustment signal to the UAV aggregation communicator based on the battery upload verification value to adjust the upload mode of the battery upload parameters.

[0028] In this embodiment, the battery upload verification value is obtained based on the battery upload parameters and the preset upload parameters. The battery upload parameters are the current battery operation data to be uploaded for the drone battery, that is, the battery upload parameters are the uploaded battery operation indicators of the drone battery, and thus correspond to the operating status of the drone battery. By collecting the battery upload parameters, it is easy to determine the operating status of the uploaded battery status indicators. The preset upload parameters are the standard uploaded battery operation data for the drone battery, that is, the preset upload parameters are the uploaded battery operation reference indicators of the drone battery, and thus correspond to the specified operating status of the drone battery. By performing hierarchical verification processing on the battery upload parameters and the preset upload parameters, it is easy to determine the differences in the current battery operation data to be uploaded for the drone battery, thereby facilitating the determination of whether there are differences in the operating status of the drone battery. After obtaining the battery upload verification value, a difference exists between the current uploaded data and the predetermined uploaded data of the drone battery. Based on this difference, the upload mode of the battery upload parameters is adjusted to ensure that the data currently to be uploaded by the drone battery uses an appropriate upload method, thus avoiding data upload conflicts, such as data upload conflicts between multiple drone batteries or between drone battery data and flight control data. All uploaded data is aggregated and transmitted via the CAN bus; see the appendix for details. Figure 2 The communication system includes: Battery Nodes (BMUs): installed in each battery module, each with an independent identification code, transmitting data, and sending CAN frames at regular intervals according to the protocol; Aggregator (PMA): managing the registration of multiple BMU nodes, frame scheduling, anomaly arbitration, and data aggregation; Flight Controller / Master Controller (FCS): the system's main controller, receiving data in a unified format and executing battery scheduling decisions; Ground Station (GCS): an optional component that remotely monitors battery status via a data link; the system adopts a star topology, with multiple BMUs communicating with the PMA via a CAN bus, and the PMA and FCS connected via a standard avionics interface.

[0029] The detailed design of the communication protocol is as follows: I. Layered Protocol Architecture 1. Physical Layer: 1) Adopts CAN 2.0B standard physical interface; 2) Supports multi-baud rate configuration (250 / 500 / 1000kbps); 3) Enhanced EMI / EMC design to improve anti-interference capability; 2. Link Layer: 1) Extended frame format (29-bit identifier); 2) Enhanced error detection and recovery mechanism; 3) Frame-level acknowledgment and retransmission mechanism; 3. Network Layer: 1) Source / destination address encoding scheme; 2) Multi-level priority arbitration mechanism; 3) Routing and forwarding rules; 4. Application Layer: 1) Data aggregation and distribution mechanism; 2) Battery parameter encoding and decoding specifications; 3) Instruction set and response mechanism.

[0030] II. Extended Frame Format Definition Optimize the CAN extended frame structure to adapt to the multi-battery communication needs of drones: CAN-ID (29-bit) structure: Data field (8-byte) structure: Detailed definition of the frame type field: "000": Control Frame - System-level Commands and Control "001": Data frame - standard parameter transmission "010": Alarm frame - Abnormal status notification "011": Query Frame - Parameter Request "100": Response frame - Query response "101": Heartbeat Frame - Online Status Maintenance "110": Synchronization Frame - Clock Synchronization "111": Reserved Priority field definition: "000": Emergency Level - Highest Priority "001": Alarm Level - High Priority "010": Control level - Medium to high priority "011": Status Level - Medium Priority "100": Diagnostic level - Low to medium priority "101"-"111": Reserved Example of function code field: “0000000”: Broadcast "0000001": Registration Request "0000010": Registration Confirmation “0000011”: Parameter reporting “0000100”: Instruction issued "0000101": Heartbeat maintained "0000110": Clock synchronization "0000111": Reset request III. Battery Data Aggregation System To address the multi-battery characteristics of drones, an aerospace-grade battery message aggregation (ABMA) structure was designed: ABMA structure { Identifier header (8 bits): Fixed mode 0xAB Parameter type (4 bits): Voltage / Current / Temperature / SOX, etc. Aggregation method (4 bits): Full / Incremental / Abnormal / Extreme value Battery bitmap (8 bits): Indicates the battery number involved. Data segment length (8 bits): Length of valid data Aggregated data segment (variable length): [Battery 1 parameters][Battery 2 parameters]...[Battery n parameters] Checksum (8 bits): CRC check } ABMA supports four aggregation methods: 1. Full aggregation: The complete set of all specified parameters for all batteries; 2. Incremental aggregation: Only includes parameters whose changes exceed the threshold; 3. Abnormal Aggregation: Only includes battery parameters in abnormal states; 4. Extreme value aggregation: Only includes the maximum / minimum value of the parameter and its corresponding battery; ABMA data structure and encapsulation diagram as shown below Figure 3 As shown.

[0031] IV. Unmanned Aerial Vehicle (UAV) Battery Communication Scheduling Mechanism Based on the flight characteristics of UAVs, design a three-dimensional scheduling strategy: 1. Flight phase-based scheduling: Takeoff phase: High-frequency sampling (100Hz), with a focus on monitoring current and power. Cruise phase: Intermediate frequency sampling (20Hz), balanced monitoring of various parameters. Landing phase: High-frequency sampling (100Hz), focusing on monitoring voltage and SOC. Ground phase: Low-frequency sampling (1Hz) to reduce power consumption 2. Scheduling based on parameter importance: Level S1 (highest): Overvoltage / undervoltage / overcurrent / overtemperature alarm S2 level (higher): Current / power extremes S3 (Medium): Voltage / SOC / Temperature S4 level (lower): Internal resistance / SOH / Number of cycles 3. Scheduling based on rate of change: Increase sampling frequency when the parameter change rate exceeds a preset threshold. Rate of change gradient adaptively adjusts sampling period Mutation detection triggers immediate reporting mechanism V. Classification and Processing of Multi-Battery Data from UAVs 1. Data hierarchical classification for flight missions Based on the requirements of drone flight missions, battery data is divided into four layers, such as... Figure 4 As shown.

[0032] 2. Adaptive Compression Technology for Unmanned Aerial Vehicles To address the limited bandwidth and computing resources of drones, lightweight compression algorithms are developed, such as... Figure 5 As shown. The corresponding adaptive algorithm selection process is as follows: Figure 6 As shown.

[0033] In the above embodiments, after collecting the battery upload parameters, the current battery operating status of the drone battery is determined. Then, the battery upload parameters are verified and compared with the standard upload parameters to determine the degree of difference in the battery operation upload data of the drone battery. Finally, based on the degree of difference in the battery operation upload data, the upload mode of the drone battery is adjusted to select the optimal upload method for the drone battery, avoid conflicts in the battery operation upload data, and effectively improve the battery data upload efficiency.

[0034] In one embodiment, acquiring the battery upload parameters for the drone battery includes: acquiring the drone battery's battery operating data, operating data fluctuation frequency, and number of abnormal operation warnings. In this embodiment, the battery upload parameters are the current battery operating data to be uploaded by the drone battery, that is, the battery upload parameters are the uploaded battery operating indicators of the drone battery, and the battery upload parameters correspond to the operating status of the drone battery. By collecting the battery upload parameters, it is easy to determine the operating status of the uploaded battery status indicators. The battery upload parameters include the drone battery's battery operating data, which are the drone battery's operating status indicators, including the drone battery's voltage, current, temperature, state, SOC, SOH, and SOP. By collecting the battery operating data, it is easy to determine the current operating status of the drone battery.

[0035] Furthermore, the battery upload parameters are subjected to hierarchical verification processing with preset upload parameters to obtain battery upload verification values, including: calculating the operational verification adjustment between battery operating data and preset operating data to obtain operational status adjustment. In this embodiment, the battery upload parameters are the current battery operating data to be uploaded for the drone battery, that is, the battery upload parameters are the uploaded battery operating indicators for the drone battery, and the battery upload parameters correspond to the operational status of the drone battery. By collecting the battery upload parameters, it is easy to determine the operational status of the uploaded battery status indicators. The preset upload parameters are the standard uploaded battery operating data for the drone battery, that is, the preset upload parameters are the uploaded battery operating reference indicators for the drone battery, and the preset upload parameters correspond to the specified operational status of the drone battery. By performing hierarchical verification processing between the battery upload parameters and the preset upload parameters, it is easy to determine the differences in the current battery operating data to be uploaded for the drone battery, thereby facilitating the determination of whether there are differences in the operational status of the drone battery. The battery upload parameters include the drone battery's operating data, which are the drone battery's working status indicators. This data includes the drone battery's voltage, current, temperature, state, SOC, SOH, and SOP. Collecting this battery operating data facilitates the determination of the drone battery's current operating status. The operating status adjustment is the adjustment value between the battery operating data and preset operating data. Specifically, the least squares difference between the battery operating data and the preset operating data is calculated to obtain the operating status adjustment. This adjustment serves as a quantification of the degree of difference in the drone battery's operating indicators, facilitating the determination of the degree of difference between the drone battery's current operating status and its safe operating status.

[0036] In another embodiment, the battery operating data also includes the fluctuation frequency of the drone battery's operating data. This fluctuation frequency reflects the frequency of changes in the drone battery's operating parameters, facilitating the determination of the drone battery's current flight status. The battery upload parameters are subjected to hierarchical verification processing with preset upload parameters to obtain a battery upload verification value. This includes calculating the fluctuation verification adjustment between the operating data fluctuation frequency and the preset fluctuation frequency to obtain a fluctuation frequency adjustment. The fluctuation frequency adjustment is the adjustment value between the battery operating data fluctuation frequency and the preset fluctuation frequency. Specifically, it involves calculating the least squares difference between the operating data fluctuation frequency and the preset fluctuation frequency to obtain the fluctuation frequency adjustment. This fluctuation frequency adjustment serves as a quantification of the rate of change in the drone battery's operating data, facilitating the determination of the degree of change in the drone battery's current operating data.

[0037] In another embodiment, the battery operation data also includes the number of abnormal operation warnings from the drone battery. The number of abnormal operation warnings refers to the number of alarms triggered by abnormal operation of the drone battery, facilitating the identification of abnormal situations occurring during the current operation of the drone battery. The battery upload parameters are subjected to hierarchical verification processing with preset upload parameters to obtain battery upload verification values. This includes: calculating the anomaly verification adjustment between the number of abnormal operation warnings and the preset number of warnings to obtain an anomaly warning adjustment. The anomaly warning adjustment is the adjustment value between the number of abnormal operation warnings and the preset number of warnings. Specifically, the least squares difference between the number of abnormal operation warnings and the preset number of warnings is calculated to obtain the anomaly warning adjustment. The anomaly warning adjustment serves as a quantification of the frequency of abnormal situations occurring in the drone battery's operation data, facilitating the determination of the severity of the current abnormalities in the drone battery's operation data.

[0038] In one embodiment, a data upload adjustment signal is sent to the drone aggregation communicator based on the battery upload verification value to adjust the upload mode of the battery upload parameters. This includes: detecting whether the operating status adjustment is greater than a preset operating status adjustment; and when the operating status adjustment is greater than the preset operating status adjustment, sending an emergency data upload signal to the drone aggregation communicator. In this embodiment, the battery upload verification value is obtained based on the battery upload parameters and the preset upload parameters. The battery upload parameters are the current battery operating data to be uploaded by the drone battery, that is, the battery upload parameters are the uploaded battery operating indicators of the drone battery, and the battery upload parameters correspond to the operating status of the drone battery. By collecting the battery upload parameters, it is convenient to determine the operating status of the uploaded battery status indicators. The preset upload parameters are the standard uploaded battery operating data of the drone battery, that is, the preset upload parameters are the uploaded battery operating reference indicators of the drone battery, and the preset upload parameters correspond to the specified operating status of the drone battery. By performing hierarchical verification processing on the battery upload parameters and the preset upload parameters, it is easy to determine the differences in the current battery operation data that the drone battery needs to upload, thereby facilitating the determination of whether there are differences in the drone battery's operating status. After obtaining the battery upload verification value, a difference exists between the current uploaded data of the drone battery and the predetermined uploaded data. Based on the differences reflected in the battery upload verification value, the upload mode of the battery upload parameters is adjusted to ensure that the data currently to be uploaded by the drone battery uses an appropriate upload method, avoiding data conflicts during upload. The battery upload parameters include the drone battery's battery operation data, which are the drone battery's working status indicators, including the drone battery's voltage, current, temperature, state, SOC, SOH, and SOP. By collecting the battery operation data, it is easy to determine the current operating status of the drone battery. The operational state adjustment is the adjustment value between the battery operational data and the preset operational data. Specifically, the least squares difference between the battery operational data and the preset operational data is calculated to obtain the operational state adjustment. This operational state adjustment serves as a quantification value of the degree of difference in the operational indicators of the drone battery, facilitating the determination of the degree of difference between the current operational status and the safe operational status of the drone battery. The preset operational adjustment is a safe quantification value of the degree of difference in the operational indicators of the drone battery. If the operational state adjustment is greater than the preset operational adjustment, it indicates that the current operational data of the drone battery exceeds a safety threshold, meaning that the uploaded data from the drone battery is the highest priority data to be transmitted. In this case, an emergency data upload signal is sent to the drone's aggregated communicator to facilitate the direct upload of the current operational data of the drone battery, ensuring the safety of the drone during flight.

[0039] Further, the step of detecting whether the operating state adjustment is greater than a preset operating adjustment includes: when the operating state adjustment is less than or equal to the preset operating adjustment, detecting whether the fluctuation frequency adjustment is greater than a preset frequency adjustment; when the fluctuation frequency adjustment is greater than the preset frequency adjustment, sending a high-frequency data upload signal to the drone aggregation communicator. In this embodiment, the battery upload verification value is obtained based on the battery upload parameters and the preset upload parameters. The battery upload parameters are the current battery operating data to be uploaded by the drone battery, that is, the battery upload parameters are the uploaded battery operating indicators of the drone battery, and the battery upload parameters correspond to the operating state of the drone battery. By collecting the battery upload parameters, it is convenient to determine the operating status of the uploaded battery status indicators. The preset upload parameters are the standard uploaded battery operating data of the drone battery, that is, the preset upload parameters are the uploaded battery operating reference indicators of the drone battery, and the preset upload parameters correspond to the specified operating state of the drone battery. By performing hierarchical verification processing on the battery upload parameters and the preset upload parameters, it is easy to determine the differences in the current battery operation data that the drone battery needs to upload, thereby facilitating the determination of whether there are differences in the drone battery's operating status. After obtaining the battery upload verification value, a difference exists between the current uploaded data of the drone battery and the predetermined uploaded data. Based on the differences reflected in the battery upload verification value, the upload mode of the battery upload parameters is adjusted to ensure that the data currently to be uploaded by the drone battery uses an appropriate upload method, avoiding data conflicts during upload. The battery upload parameters include the drone battery's battery operation data, which are the drone battery's working status indicators, including the drone battery's voltage, current, temperature, state, SOC, SOH, and SOP. By collecting the battery operation data, it is easy to determine the current operating status of the drone battery. The operational state adjustment is the adjustment value between the battery operating data and the preset operating data. Specifically, the least squares difference between the battery operating data and the preset operating data is calculated to obtain the operational state adjustment. The operational state adjustment serves as a quantification value of the degree of difference in the operating indicators of the drone battery, facilitating the determination of the degree of difference between the current operating condition and the safe operating condition of the drone battery. The preset operational adjustment is a safety-quantified value of the degree of difference in the operating indicators of the drone battery. If the operational state adjustment is less than or equal to the preset operational adjustment, it indicates that the current operating condition of the drone battery is a safe condition.The fluctuation frequency adjustment is the adjustment value between the fluctuation frequency of the battery operating data and the preset fluctuation frequency. Specifically, the least squares difference between the operating data fluctuation frequency and the preset fluctuation frequency is calculated to obtain the fluctuation frequency adjustment. The fluctuation frequency adjustment serves as a quantification value of the rate of change of the drone battery's operating data, facilitating the determination of the degree of change in the current operating data of the drone battery. The preset frequency adjustment is a standard quantification value of the rate of change of the drone battery's operating data. If the fluctuation frequency adjustment is greater than the preset frequency adjustment, it indicates that the operating data of the drone battery is fluctuating significantly, that is, the data of the drone battery is changing rapidly, which also indicates that the drone is in a rapid flight state, such as when the drone is in a takeoff or landing flight attitude. At this time, a high-frequency data upload signal is sent to the drone's aggregated communicator. The drone battery data is transmitted with high priority. Specifically, the drone battery data is sampled at 100Hz through the CAN bus. During the takeoff phase, the fluctuation frequency of current and power is monitored, and during the landing phase, the fluctuation frequency of voltage and SOC is monitored.

[0040] Furthermore, after detecting whether the fluctuation frequency adjustment is greater than a preset frequency adjustment, the method further includes: when the fluctuation frequency adjustment is less than or equal to the preset frequency adjustment, detecting whether the operating state adjustment is greater than the static operating adjustment; when the operating state adjustment is greater than the static operating adjustment, sending a data intermediate frequency upload signal to the drone aggregation communicator. In this embodiment, the battery upload verification value is obtained based on the battery upload parameters and the preset upload parameters. The battery upload parameters are the current battery operating data to be uploaded by the drone battery, that is, the battery upload parameters are the uploaded battery operating indicators of the drone battery, and the battery upload parameters correspond to the operating state of the drone battery. By collecting the battery upload parameters, it is convenient to determine the operating status of the uploaded battery status indicators. The preset upload parameters are the standard uploaded battery operating data of the drone battery, that is, the preset upload parameters are the uploaded battery operating reference indicators of the drone battery, and the preset upload parameters correspond to the specified operating state of the drone battery. By performing hierarchical verification processing on the battery upload parameters and the preset upload parameters, it is easy to determine the differences in the current battery operation data that the drone battery needs to upload, thereby facilitating the determination of whether there are differences in the drone battery's operating status. After obtaining the battery upload verification value, a difference exists between the current uploaded data of the drone battery and the predetermined uploaded data. Based on the differences reflected in the battery upload verification value, the upload mode of the battery upload parameters is adjusted to ensure that the data currently to be uploaded by the drone battery uses an appropriate upload method, avoiding data conflicts during upload. The battery upload parameters include the drone battery's battery operation data, which are the drone battery's working status indicators, including the drone battery's voltage, current, temperature, state, SOC, SOH, and SOP. By collecting the battery operation data, it is easy to determine the current operating status of the drone battery. The operational state adjustment is the adjustment value between the battery operational data and the preset operational data. Specifically, the least squares difference between the battery operational data and the preset operational data is calculated to obtain the operational state adjustment. The operational state adjustment serves as a quantification value of the degree of difference in the operational indicators of the drone battery, facilitating the determination of the degree of difference between the current operational status and the safe operational status of the drone battery. The fluctuation frequency adjustment is the adjustment value between the fluctuation frequency of the battery operational data and the preset fluctuation frequency. Specifically, the least squares difference between the fluctuation frequency of the operational data and the preset fluctuation frequency is calculated to obtain the fluctuation frequency adjustment. The fluctuation frequency adjustment serves as a quantification value of the rate of change of the operational data of the drone battery, facilitating the determination of the degree of change in the current operational data of the drone battery.The preset frequency adjustment is a standard quantified value of the rate of change of the drone battery's operating data. If the fluctuation frequency adjustment is less than or equal to the preset frequency adjustment, it indicates that the drone battery's operating data changes little and is within the normal fluctuation range. The static operating adjustment is a static quantified value of the degree of difference in the drone battery's operating indicators. If the operating state adjustment is greater than the static operating adjustment, it indicates that the drone battery's operating data exceeds the normal variation range, meaning the drone is in the cruise phase. At this time, a data intermediate frequency upload signal is sent to the drone's aggregated communicator. The drone battery data is transmitted with standard priority. Specifically, the drone battery data is sampled at 20Hz via the CAN bus, and all data of the drone battery are monitored in a balanced manner; that is, all data are monitored.

[0041] Furthermore, the process of detecting whether the operational status adjustment is greater than the static operational adjustment includes: when the operational status adjustment is less than or equal to the static operational adjustment, detecting whether the abnormal warning adjustment is greater than the preset abnormal adjustment; when the abnormal warning adjustment is greater than the preset abnormal adjustment, sending a low-frequency data upload signal to the drone aggregation communicator. In this embodiment, the battery upload verification value is obtained based on the battery upload parameters and the preset upload parameters. The battery upload parameters are the current battery operation data to be uploaded by the drone battery, that is, the battery upload parameters are the uploaded battery operation indicators of the drone battery, and the battery upload parameters correspond to the operational status of the drone battery. By collecting the battery upload parameters, it is convenient to determine the operational status of the uploaded battery status indicators. The preset upload parameters are the standard uploaded battery operation data of the drone battery, that is, the preset upload parameters are the uploaded battery operation reference indicators of the drone battery, and the preset upload parameters correspond to the specified operational status of the drone battery. By performing hierarchical verification processing on the battery upload parameters and the preset upload parameters, it is easy to determine the differences in the current battery operation data that the drone battery needs to upload, thereby facilitating the determination of whether there are differences in the drone battery's operating status. After obtaining the battery upload verification value, a difference exists between the current uploaded data of the drone battery and the predetermined uploaded data. Based on the differences reflected in the battery upload verification value, the upload mode of the battery upload parameters is adjusted to ensure that the data currently to be uploaded by the drone battery uses an appropriate upload method, avoiding data conflicts during upload. The battery upload parameters include the drone battery's battery operation data, which are the drone battery's working status indicators, including the drone battery's voltage, current, temperature, state, SOC, SOH, and SOP. By collecting the battery operation data, it is easy to determine the current operating status of the drone battery. The operational state adjustment is the adjustment value between the battery operational data and the preset operational data. Specifically, the least squares difference between the battery operational data and the preset operational data is calculated to obtain the operational state adjustment. The operational state adjustment serves as a quantification value of the degree of difference in the operational indicators of the drone battery, facilitating the determination of the degree of difference between the current operational status and the safe operational status of the drone battery. The fluctuation frequency adjustment is the adjustment value between the fluctuation frequency of the battery operational data and the preset fluctuation frequency. Specifically, the least squares difference between the fluctuation frequency of the operational data and the preset fluctuation frequency is calculated to obtain the fluctuation frequency adjustment. The fluctuation frequency adjustment serves as a quantification value of the rate of change of the operational data of the drone battery, facilitating the determination of the degree of change in the current operational data of the drone battery.The preset frequency adjustment is a standardized quantification of the rate of change in the drone battery's operating data. A fluctuation frequency adjustment less than or equal to the preset frequency adjustment indicates that the drone battery's operating data changes relatively little and is within the normal fluctuation range. The static operation adjustment is a static quantification of the degree of difference in the drone battery's operating indicators. An operation state adjustment less than or equal to the static operation adjustment indicates that the drone battery's operating data is within the normal variation range. The anomaly warning adjustment is the adjustment value between the number of operational anomaly warnings and the preset number of warnings. Specifically, the least squares difference between the number of operational anomaly warnings and the preset number of warnings is calculated to obtain the anomaly warning adjustment. This anomaly warning adjustment serves as a quantification of the frequency of abnormal situations occurring in the drone battery's operating data, facilitating the determination of the severity of the current anomaly in the drone battery's operating data. The preset anomaly adjustment is a reference quantification value for the frequency of abnormal situations in the drone battery's operating data. If the anomaly warning adjustment is less than or equal to the preset anomaly adjustment, it indicates that the number of abnormalities in the drone battery's operating data is too low, which means that the drone battery is in a stable state and that the drone is currently on the ground. At this time, a low-frequency data upload signal is sent to the drone's aggregated communicator. The drone battery data is transmitted with low-frequency priority. Specifically, the drone battery data is sampled at 1Hz through the CAN bus to reduce the drone battery power consumption.

[0042] In another embodiment, when the anomaly warning adjustment exceeds a preset anomaly adjustment, a CAN bus transmission termination signal is sent to the UAV aggregation communicator to avoid excessive abnormal data consuming CAN bus bandwidth. All the aforementioned preset variables are set in a database for easy and timely retrieval, and different preset variables are placed in different storage units, i.e., in different storage stacks. Furthermore, battery operating data, operating data fluctuation frequency, and the number of operating anomaly warnings can be collected by the corresponding processor, for example, through the BMS chip of the battery data acquisition module.

[0043] In one embodiment, this disclosure also relates to a drone battery data upload communication monitoring device, which employs the drone battery data upload communication monitoring method described in any of the above embodiments. The device includes a battery data acquisition module, an upload verification processing module, and an upload adjustment module. The battery data acquisition module is used to acquire battery upload parameters of the drone battery. The upload verification processing module is used to perform hierarchical verification processing on the preset upload parameters of the battery upload parameters to obtain a battery upload verification value. The upload adjustment module is used to send a data upload adjustment signal to the drone aggregation communicator according to the battery upload verification value to adjust the upload mode of the battery upload parameters.

[0044] In this embodiment, after the battery data acquisition module collects the battery upload parameters, it determines the current battery operating status of the drone battery. Then, the upload verification processing module compares the battery upload parameters with the standard upload parameters to determine the degree of difference in the uploaded battery operating data. Finally, the upload adjustment module adjusts the upload mode of the drone battery according to the degree of difference in the uploaded battery operating data to select the optimal upload method for the drone battery, avoid conflicts in the uploaded battery operating data, and effectively improve the battery data upload efficiency.

[0045] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data such as multimodal sintering state parameters, sintering weighted fusion characteristics, sintering dynamic distribution values, and sintering failure signals. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for monitoring and uploading UAV battery data.

[0046] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0047] In one embodiment, this application also provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0048] In one embodiment, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method embodiments.

[0049] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0050] The embodiments described above are merely illustrative of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these all fall within the protection scope of this disclosure. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for monitoring and uploading battery data from a drone, characterized in that, include: Obtain the battery upload parameters for the drone battery; The battery upload parameters are compared with preset upload parameters in a hierarchical verification process to obtain the battery upload verification value. Based on the battery upload verification value, a data upload adjustment signal is sent to the drone aggregation communicator to adjust the upload mode of the battery upload parameters.

2. The UAV battery data upload communication monitoring method according to claim 1, characterized in that, The battery upload parameters for obtaining the drone battery include: Acquire battery operation data, operation data fluctuation frequency, and the number of operation anomaly warnings for the drone battery.

3. The UAV battery data upload communication monitoring method according to claim 2, characterized in that, The battery upload parameters are compared with preset upload parameters using a hierarchical verification process to obtain a battery upload verification value, including: Calculate the operational verification adjustment between the battery operating data and the preset operating data to obtain the operational state adjustment; And / or, calculate the fluctuation verification adjustment between the fluctuation frequency of the running data and the preset fluctuation frequency to obtain the fluctuation frequency adjustment; And / or, calculate the exception verification adjustment between the number of runtime exception warnings and the preset number of warnings to obtain the exception warning adjustment.

4. The UAV battery data upload communication monitoring method according to claim 3, characterized in that, Based on the battery upload verification value, a data upload adjustment signal is sent to the drone aggregation communicator to adjust the upload mode of the battery upload parameters, including: Detect whether the operational status adjustment is greater than the preset operational adjustment; When the operational status adjustment exceeds the preset operational adjustment, an emergency data upload signal is sent to the UAV aggregation communicator.

5. The UAV battery data upload communication monitoring method according to claim 4, characterized in that, The step of detecting whether the operational state adjustment is greater than the preset operational adjustment further includes: When the operating state adjustment is less than or equal to the preset operating adjustment, it is detected whether the fluctuation frequency adjustment is greater than the preset frequency adjustment. When the fluctuation frequency adjustment is greater than the preset frequency adjustment, a high-frequency data upload signal is sent to the UAV aggregation communicator.

6. The UAV battery data upload communication monitoring method according to claim 5, characterized in that, The process further includes detecting whether the fluctuation frequency adjustment is greater than a preset frequency adjustment, followed by: When the fluctuation frequency adjustment is less than or equal to the preset frequency adjustment, it is detected whether the operating state adjustment is greater than the static operating adjustment. When the operational adjustment is greater than the static operational adjustment, a data intermediate frequency upload signal is sent to the UAV aggregation communicator.

7. The UAV battery data upload communication monitoring method according to claim 6, characterized in that, The process includes checking whether the operational adjustment is greater than the static adjustment, followed by: When the running status adjustment is less than or equal to the static running adjustment, check whether the abnormal warning adjustment is less than or equal to the preset abnormal adjustment. When the abnormal warning adjustment is less than or equal to the preset abnormal adjustment, a low-frequency data upload signal is sent to the drone aggregation communicator.

8. A drone battery data upload communication monitoring device, wherein the drone battery data upload communication monitoring device adopts the drone battery data upload communication monitoring method as described in any one of claims 1 to 7, characterized in that, include: A battery data acquisition module, which is used to acquire the battery upload parameters of the drone battery; An upload verification processing module is used to perform hierarchical verification processing on the preset upload parameters of the battery upload parameters to obtain the battery upload verification value. An upload adjustment module is used to send a data upload adjustment signal to the UAV aggregation communicator based on the battery upload verification value, so as to adjust the upload mode of the battery upload parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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